---
title: "Who cites Qingyu Chen — 151 papers of our library"
description: "151 papers of the Elamur Research library cite the works of Qingyu Chen, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/qingyu-chen/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/qingyu-chen/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Qingyu Chen](https://md.research.elamur.ai/free/en/authors/qingyu-chen/) / cited by

# Who cites Qingyu Chen

151 citations of their works from 151 papers of our library (of the 149,439 whose bibliographies we read) · 39 with a page here, the most cited first · [← Qingyu Chen](https://md.research.elamur.ai/free/en/authors/qingyu-chen/)

1. **[CORD-19: The COVID-19 Open Research Dataset](https://md.research.elamur.ai/free/en/papers/wang-2020-cord-19-covid-19-open/) [Workshop on NLP for COVID-19 at ACL](https://md.research.elamur.ai/free/en/venues/nlpcovid19/)**Lucy Lu Wang, Kyle Lo, Yoganand Chandrasekhar, et al.*2020 · 695 citations*
2. [**ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs arXiv:2307.16789**Yujia Qin, Shihao Liang, Yining Ye, et al.*2023 · 589 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/)
3. [**Retrieval-Augmented Generation for AI-Generated Content: A Survey arXiv:2402.19473**Penghao Zhao, Hailin Zhang, Qinhan Yu, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-retrieval-augmented-generation-ai-generated/)
4. **[MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 246 citations*
5. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
6. **[ToolQA: A Dataset for LLM Question Answering with External Tools](https://md.research.elamur.ai/free/en/papers/zhuang-2023-toolqa-dataset-llm-question-answering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuchen Zhuang, Yue Yu, Kuan Wang, et al.*2023 · 182 citations*
7. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
8. **[ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings](https://md.research.elamur.ai/free/en/papers/hao-2023-toolkengpt-augmenting-frozen-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shibo Hao, Tianyang Liu, Zhen Wang, et al.*2023 · 147 citations*
9. [**BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text arXiv:2403.18421**Elliot Bolton, Abhinav Venigalla, Michihiro Yasunaga, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/bolton-2024-biomedlm-2-7b-parameter-language/)
10. [**Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks arXiv:2404.00376**Hyunjae Kim, Hyeon Hwang, Jiwoo Lee, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-small-language-models-learn-enhanced/)
11. [**Evaluation of OpenAI o1: Opportunities and Challenges of AGI arXiv:2409.18486**Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.*2024 · 64 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-evaluation-openai-o1-opportunities-challenges/)
12. **[Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning](https://md.research.elamur.ai/free/en/papers/yang-2024-self-distillation-bridges-distribution-gap/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaorui Yang, Tianyu Pang, Haozhe Feng, et al.*2024 · 63 citations*
13. **[SciAgent: Tool-augmented Language Models for Scientific Reasoning](https://md.research.elamur.ai/free/en/papers/ma-2024-sciagent-tool-augmented-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yubo Ma, Zhibin Gou, Junheng Hao, et al.*2024 · 55 citations*
14. **[ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios](https://md.research.elamur.ai/free/en/papers/ye-2025-tooleyes-fine-grained-evaluation-tool/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Junjie Ye, Guanyu Li, SongYang Gao, et al.*2025 · 35 citations*
15. [**Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning arXiv:2512.20848**NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.*2025 · 27 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-3-nano-open-efficient/)
16. [**Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation arXiv:2603.19220**Zhuolin Yang, Zihan Liu, Yang Chen, et al.*2026 · 16 citations*](https://md.research.elamur.ai/free/en/papers/yang-2026-nemotron-cascade-2-post-training/)
17. **[Alignment for Efficient Tool Calling of Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2025-alignment-efficient-tool-calling-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hongshen Xu, Zihan Wang, Zichen Zhu, et al.*2025 · 13 citations*
18. **[Efficient Tool Use with Chain-of-Abstraction Reasoning](https://md.research.elamur.ai/free/en/papers/gao-2025-efficient-tool-use-chain-abstraction/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Silin Gao, Jane Dwivedi-Yu, Ping Yu, et al.*2025 · 13 citations*
19. **[MultiLoKo: a multilingual local knowledge benchmark for LLMs spanning 31 languages](https://md.research.elamur.ai/free/en/papers/hupkes-2025-multiloko-multilingual-local-knowledge-benchmark/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Dieuwke Hupkes, Nikolay Bogoychev*2025 · 12 citations*
20. [**BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical Science arXiv:2407.00466**Xinna Lin, Siqi Ma, Junjie Shan, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-biokgbench-knowledge-graph-checking-benchmark/)
21. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
22. **[POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering](https://md.research.elamur.ai/free/en/papers/xu-2026-polychartqa-benchmarking-large-vision-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yichen Xu, Liangyu Chen, Liang Zhang, et al.*2026 · 2 citations*
23. **[AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-agenticeval-agentic-self-evolving-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yixu Wang, Xin Wang, Yang Yao, et al.*2026 · 1 citation*
24. **[AMALIA: A Fully Open Large Language Model for European Portuguese](https://md.research.elamur.ai/free/en/papers/simplicio-2026-amalia-fully-open-large-language/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Afonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos, et al.*2026 · 1 citation*
25. **[ARISE: An Adaptive Resolution-Aware Metric for Test-Time Scaling Evaluation in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/yin-2026-arise-adaptive-resolution-aware-metric/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangyue Yin, Qiushi Sun, Zhiyuan Zeng, et al.*2026 · 1 citation*
26. **[Serbian SuperGLUE: Towards an Evaluation Benchmark for South Slavic Language Models](https://md.research.elamur.ai/free/en/papers/perovic-2026-serbian-superglue-evaluation-benchmark-south/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Mitar Perovic, Teodora Mihajlov*2026 · 1 citation*
27. **[A Comparative Study of Multilingual Fine-tuning and Prompting for Automatic Text Readability Classification in Galician](https://md.research.elamur.ai/free/en/papers/rey-2026-comparative-study-multilingual-fine-tuning/) [Joint Workshop on Readability and Text Simplification (READIxTSAR) @ LREC](https://md.research.elamur.ai/free/en/venues/readi/)**Sandra Rodríguez Rey, Marcos Garcia*2026*
28. **[Charting the European LLM Benchmarking Landscape: A New Taxonomy and Registry](https://md.research.elamur.ai/free/en/papers/vintar-2026-charting-european-llm-benchmarking-landscape/) [Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LREC](https://md.research.elamur.ai/free/en/venues/llms4ssh/)**Spela Vintar, Mojca Brglez, Taja Kuzman Pungeršek, et al.*2026*
29. **[Expert Calibration Lens for Pruning Mixture of Experts](https://md.research.elamur.ai/free/en/papers/salim-2026-expert-calibration-lens-pruning-mixture/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luis Frentzen Salim, Chia-Chun Wu, Tran Van Nhiem, et al.*2026*
30. **[From Narrow Unlearning to Emergent Misalignment in LLMs](https://md.research.elamur.ai/free/en/papers/mushtaq-2026-narrow-unlearning-emergent-misalignment-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erum Mushtaq, Anil Ramakrishna, Satyapriya Krishna, et al.*2026*
31. **[Generation of Instruction and Preference Dataset for Improving Japanese Instruction Following in LLMs](https://md.research.elamur.ai/free/en/papers/moriyama-2026-generation-instruction-preference-dataset-improving/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kei Moriyama, Takashi Kodama, Kouta Nakayama*2026*
32. **[How to Improve LLMs' Performance on Specific Languages: A Perspective on LLM-Derived Language Similarity](https://md.research.elamur.ai/free/en/papers/shi-2026-how-improve-llms-performance-specific/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinhe Shi, Qingcheng Zeng, Weihao Xuan, et al.*2026*
33. **[I Understand How You Feel: Enhancing Deeper Emotional Support Through Multilingual Emotional Validation in Dialogue System](https://md.research.elamur.ai/free/en/papers/pang-2026-i-understand-how-you-feel/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Zi Haur Pang, Yahui Fu, Koji Inoue, et al.*2026*
34. **[Is Biomedical Specialization Still Worth It? Insights from Domain-Adaptive Language Modelling with a New French Health Corpus](https://md.research.elamur.ai/free/en/papers/mannion-2026-is-biomedical-specialization-still-worth/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aidan Mannion, Cécile Macaire, Armand Violle, et al.*2026*
35. **[KGRxn-LLM: Knowledge Graph Enhanced Large Language Models for Molecular Reaction Reasoning](https://md.research.elamur.ai/free/en/papers/liu-2026-kgrxn-llm-knowledge-graph-enhanced/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Weichen Liu, Qiyao Xue, Yuyang Wu, et al.*2026*
36. **[LLMs as annotators of credibility assessment in Danish asylum decisions: evaluating classification performance and errors beyond aggregated metrics](https://md.research.elamur.ai/free/en/papers/renaux-2026-llms-as-annotators-credibility-assessment/) [Linguistic Annotation Workshop (LAW)](https://md.research.elamur.ai/free/en/venues/law/)**Galadrielle Humblot-Renaux, Mohammad N. S. Jahromi, Rohat Bakuri-Jørgensen, et al.*2026*
37. **[mmPISA-bench: Do LLMs Reason Equally Well Across 43 Languages?](https://md.research.elamur.ai/free/en/papers/sapenov-2026-mmpisa-bench-do-llms-reason/) [Workshop on Multilinguality in the Era of Large Language Models](https://md.research.elamur.ai/free/en/venues/mellm/)**Yerzhan Sapenov, Jaromir Savelka*2026*
38. **[Reclaiming African Voices: Surveying Indigenous Writing Systems for Inclusive NLP](https://md.research.elamur.ai/free/en/papers/traore-2026-reclaiming-african-voices-surveying-indigenous/) [Resources for African Indigenous Languages (RAIL) @ LREC](https://md.research.elamur.ai/free/en/venues/rail/)**Mamady Traore, Ngoc Tan Le, Fatiha Sadat*2026*
39. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述) Acta Automatica Sinica (自动化学报)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)

112 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/qingyu-chen/) — Qingyu Chen